Harnessing Automation for Quality Assurance in Medical Imaging: RPA and Deep Learning Techniques

Abstract

Medical imaging plays a critical role in diagnosing and treating various health conditions, necessitating rigorous quality assurance processes to ensure accurate and reliable results. However, the increasing volume and complexity of medical imaging data present challenges for manual quality assessment. Harnessing automation through Robotic Process Automation (RPA) and Deep Learning techniques offers a promising solution to streamline quality assurance workflows, enhance efficiency, and improve patient outcomes. This paper provides an overview of RPA and Deep Learning applications in medical imaging quality assurance, discusses their benefits and challenges, and explores future directions in this rapidly evolving field.